Enterprise Data Architect

Harnham; Chicago (IL); On-site; USD 150,000 - 180,000; Full time

Job summary

A leading architecture and design firm in Chicago is seeking an experienced Enterprise Data Architect to establish a scalable data infrastructure. This senior-level position requires over 10 years of experience and expertise in Databricks and AWS. The architect will design and implement the firm's Data Lakehouse architecture, moving towards enterprise-level analytics and AI initiatives. This role offers a unique opportunity to impact the firm’s data landscape and analytics capabilities significantly.

Qualifications

• 10+ years of experience as a Senior Architect.
• Proven expertise in enterprise data architecture and cloud platforms.
• Hands-on experience in building platforms from the ground up.

Responsibilities

• Architect and build Databricks infrastructure on AWS.
• Design enterprise lakehouse architecture (Databricks + Snowflake).
• Drive cost optimization and scalability strategies.

Skills

Databricks

AWS

Snowflake

Cost optimization and platform strategy

Greenfield build experience

Job description

A globally recognized architecture and design firm responsible for some of the most iconic buildings and urban environments in the world is looking for an Enterprise Data Architect to establish the enterprise data infrastructure foundation. Our client has deep internal data knowledge and a validated Databricks POC but lacks a senior architect to design and implement a scalable, production-grade lakehouse. This role moves the platform from concept to enterprise reality.

Key Differentiators vs Competitors:

• True greenfield data architecture mandate
• Direct partnership with senior leadership
• High-impact role tied to analytics, AI, and design outcomes
• Tangible, lasting impact on skylines and cities globally

Core Purpose:

Design and implement the firm’s enterprise Data Lakehouse architecture, moving the organization from POC to MVP and establishing the foundation for scalable analytics, AI/ML, and cost-efficient data operations.

Key Responsibilities & Ownership Areas:

• Architect and build Databricks infrastructure on AWS
• Design enterprise lakehouse architecture (Databricks + Snowflake)
• Define patterns for moving data across enterprise systems and design platforms
• Partner with Info Systems (platform ownership) and DevOps (infrastructure support) teams
• Drive cost optimization and scalability strategies
• Establish architectural standards, governance models, and technical roadmaps
• Work directly with senior leadership, finance, and business operations
• Help steer the long‑term vision for analytics and AI across the firm

Key Projects in First 6–12 Months:

• Transition Databricks from POC to MVP
• Define the enterprise data framework and game plan
• Design what the future data lakehouse enables across the business
• Build the foundation for transformational analytics and AI initiatives

Target Seniority / Years of Experience:

Senior Architect – 10+ years

Domain or Functional Expertise:

Enterprise data architecture, cloud platforms, analytics infrastructure

Ideal Company / Industry Background:

Proven experience building platforms from the ground up, either solo or in small teams. AEC experience is a plus but not required; practical, hands‑on execution is key.

Must-Have Skills:

• Databricks (critical)
• AWS
• Snowflake
• Cost optimization and platform strategy
• Greenfield build experience

Nice‑to‑Have Skills:

• Exposure to design or engineering data
• Experience partnering with DevOps teams
• Interest in analytics, ML, or AI enablement